Protein Peeling 3 D

Protein Peeling 3 D partitions protein 3D structures into small, compact Protein Units (PUs) to analyze structural organization and inform functional and stability-related interpretations.

Key Features:

• Identification of Protein Units (PUs): Identifies small, compact units within protein 3D structures using an iterative splitting algorithm.
• Contact probability matrix: Constructs a contact probability matrix from inter-Calpha distances translated into probabilities.
• Hierarchical clustering: Uses the contact probability matrix as the basis for a hierarchical clustering approach to partition the structure.
• Iterative splitting with partition index: Iteratively divides units into 2 or 3 subunits at each step based on a partition index that evaluates structural independence of newly defined subunits.
• Global quality metric R: Computes an entropy-derived squared correlation R to assess the global quality of the protein structure dissection.
• Domain identification: Includes capabilities for identifying structural domains.
• Detection of unstructured terminal elements: Detects unstructured terminal elements.
• Stability evaluation: Evaluates the stability of protein unit structures.
• Comparative performance: Demonstrates improved performance compared to other splitting algorithms.

Scientific Applications:

• Structural analysis: Detailed dissection of protein 3D structures to understand structural organization and functional mechanisms.
• Domain and disorder characterization: Identification and characterization of protein domains and unstructured regions.
• Stability assessment and engineering: Evaluation of protein unit stability with implications for protein engineering and drug design.

Methodology:

Builds a contact probability matrix from inter-Calpha distances converted to probabilities; applies hierarchical clustering as an iterative splitting algorithm; at each step divides units into 2 or 3 subunits using a partition index that evaluates structural independence; computes an entropy-derived squared correlation R to assess global dissection quality.